Data has been collected for many reasons and put to many purposes. It is often desirable to aggregate collected data in order to discern changes. For example, many modern printers record running usage data over the lifetime of the device. This usage data may be accessed periodically to discern how many pages have been printed between access times.
Many conventional data collection and aggregation techniques have included manual collection of data and input of the data into a database. Both manual collection and data entry are time consuming, labor intensive, and prone to human error.
Automated collection and entry techniques have been developed to overcome these shortcomings of manual collection and entry. Conventional data collection and entry techniques receive data into a database where the data may be manipulated to achieve a desired output. Although these conventional automated techniques reduce the time and labor required for data collection and entry, errors still frequently occur.
One of the main causes of error in these conventional techniques is the lack of accuracy and integrity controls. For example, if data is repeatedly received from a device having a particular address and the address is subsequently assigned to a different device, inaccurate data may be recorded.
Furthermore, conventional data collection and entry techniques are usually not portable. That is, the collection database must be able to directly access the devices having the data to be recorded. Often, such access is not convenient, desirable, or possible. In such cases, it would be more desirable to have a data collection tool that has access to the devices. The data collection tool may then record the information and transfer a record of the information to a managing tool for aggregation into a database.